The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
Imprint of assortative mating on the human genome
Open accessPublished version of a preprint
Abstract
Preference for mates with similar phenotypes; that is, assortative mating, is widely observed in humans 1-5 and has evolutionary consequences 6-8. Under Fisher's classical theory 6, assortative mating is predicted to induce a signature in the genome at trait-associated loci that can be detected and quantified. Here, we develop and apply a method to quantify assortative mating on a specific trait by estimating the correlation (θ) between genetic predictors of the trait from single nucleotide polymorphisms on odd- versus even-numbered chromosomes. We show by theory and simulation that the effect of assortative mating can be quantified in the presence of population stratification. We applied this approach to 32 complex traits and diseases using single nucleotide polymorphism data from ~400,000 unrelated individuals of European ancestry. We found significant evidence of assortative mating for height (θ = 3.2%) and educational attainment (θ = 2.7%), both of which were consistent with theoretical predictions. Overall, our results imply that assortative mating involves multiple traits and affects the genomic architecture of loci that are associated with these traits, and that the consequence of mate choice can be detected from a random sample of genomes.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The primary explanation is likely AM, which is strong for EA and height25,31, although IGEs that are positively correlated with DGEs could also contribute3.”
From Family-GWAS reveals effects of environment and mating on genetic associations (2024) · cites this paper as [25]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“However, there is growing evidence that GWAS associations for some phenotypes estimated from samples of unrelated individuals also capture effects of demography7,8 (assortative mating9–11 and population stratification12) and indirect genetic effects of relatives13–19 (Fig. 1).”
From Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects (2022) · cites this paper as [11]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
A global reference for human genetic variation
The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247
The UK Biobank resource with deep phenotyping and genomic data
Bycroft, C., Freeman, C., Petkova, D., Band, G., Elliott, L. T., Sharp, K., Motyer, A., Vukcevic, D., Delaneau, O., O’Connell, J., et al. (2018) · Nature · doi:10.1038/s41586-018-0579-z · Cited by 8,876
GCTA: a tool for genome-wide complex trait analysis
Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.11.011 · Cited by 8,279
Self-citationXV.—The Correlation between Relatives on the Supposition of Mendelian Inheritance.
Fisher, R. A. (1919) · Transactions of the Royal Society of Edinburgh · doi:10.1017/s0080456800012163 · Cited by 4,387 · cited 1×
“In conclusion, our study provides empirical quantification of GPD induced among trait-associated alleles, a phenomenon predicted by theory exactly a century ago by Fisher (1918)1.”
BackgroundAn introduction to population genetics theory
Crow, J. F., & Kimura, M. (1970) · Medical Entomology and Zoology · Cited by 4,223
Integrating common and rare genetic variation in diverse human populations
The International HapMap 3 Consortium (2010) · Nature · doi:10.1038/nature09298 · Cited by 3,026
An Expanded View of Complex Traits: From Polygenic to Omnigenic
Boyle, E. A., Li, Y. I., & Pritchard, J. K. (2017) · Cell · doi:10.1016/j.cell.2017.05.038 · Cited by 2,851
A reference panel of 64,976 haplotypes for genotype imputation
the Haplotype Reference Consortium (2016) · Nature Genetics · doi:10.1038/ng.3643 · Cited by 2,836
23andMe Research Team, Lee, J. J., COGENT (Cognitive Genomics Consortium), Social Science Genetic Association Consortium, Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, M., Nguyen-Viet, T. A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0147-3 · Cited by 2,470
Self-citationYengo, L., Sidorenko, J., Kemper, K. E., Zheng, Z., Wood, A. R., Weedon, M. N., Frayling, T. M., Hirschhorn, J. N., Yang, J., & Visscher, P. M. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy271 · Cited by 2,393
Self-citationBlundell, J. E., Baker, J. L., Boyland, E. J., Blaak, E. E., Charzewska, J., Henauw, S. D., Frühbeck, G., González‐Gross, M., Hebebrand, J., Holm, L., et al. (2017) · Obesity Facts · doi:10.1159/000455952 · Cited by 1,983
The Electronic Medical Records and Genomics (eMERGE) Consortium, Wood, A. R., The MIGen Consortium, The PAGE Consortium, Study, T. L. C., Esko, T., Yang, J., Vedantam, S., Pers, T. H., Gustafsson, S., et al. (2014) · Nature Genetics · doi:10.1038/ng.3097 · Cited by 1,853 · cited 1×
“For height, we used estimated effect sizes, from summary statistics of the latest GWAS meta-analysis of the GIANT consortium (Wood et al. 2014)25, of 9,447 near independent HapMap3 (HM3) SNPs selected using the LD clumping algorithm implemented in the software PLINK26 (linkage disequilibrium (LD)…”
MethodSelf-citationGenome-wide association study identifies 74 loci associated with educational attainment
Okbay, A., Beauchamp, J. P., Fontana, M. A., Lee, J. J., Pers, T. H., Rietveld, C. A., Turley, P., Chen, G.-B., Emilsson, V., Meddens, S. F. W., et al. (2016) · Nature · doi:10.1038/nature17671 · Cited by 1,297
Self-citationFive Decades of Educational Assortative Mating
Mare, R. D. (1991) · American Sociological Review · doi:10.2307/2095670 · Cited by 1,162
Introduction to sample size determination and power analysis for clinical trials
Lachin, J. M. (1981) · Controlled Clinical Trials · doi:10.1016/0197-2456(81)90001-5 · Cited by 1,012
Genome-wide genetic data on ~500,000 UK Biobank participantsPreprint
Bycroft, C., Freeman, C., Petkova, D., Band, G., Elliott, L. T., Sharp, K., Motyer, A., Vukcevic, D., Delaneau, O., O’Connell, J., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/166298 · Cited by 622
UK Biobank: Current status and what it means for epidemiology
Allen, N., Sudlow, C., Downey, P., Peakman, T., Danesh, J., Elliott, P., Gallacher, J., Green, J., Matthews, P., Pell, J., et al. (2012) · Health Policy and Technology · doi:10.1016/j.hlpt.2012.07.003 · Cited by 521
Sniekers, S., Stringer, S., Watanabe, K., Jansen, P. R., Coleman, J. R. I., Krapohl, E., Taskesen, E., Hammerschlag, A. R., Okbay, A., Zabaneh, D., et al. (2017) · Nature Genetics · doi:10.1038/ng.3869 · Cited by 490
Self-citationA population genetic signal of polygenic adaptation
Berg, J. J., & Coop, G. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004412 · Cited by 487
Kemp, J. P., Morris, J. A., Medina‐Gómez, C., Forgetta, V., Warrington, N. M., Youlten, S. E., Zheng, J., Gregson, C. L., Grundberg, E., Trajanoska, K., et al. (2017) · Nature Genetics · doi:10.1038/ng.3949 · Cited by 470
Model-fitting approaches to the analysis of human behaviour
Eaves, L. J., Last, K. A., Young, P. A., & Martin, N. G. (1978) · Heredity · doi:10.1038/hdy.1978.101 · Cited by 457
Jiang, Y., Bolnick, D. I., & Kirkpatrick, M. (2013) · The American Naturalist · doi:10.1086/670160 · Cited by 427
The PRACTICAL Consortium, Day, F. R., kConFab Investigators, AOCS Investigators, Scotland, G., EPIC-InterAct Consortium, Study, L. C., Ruth, K. S., Thompson, D. J., Lunetta, K. L., et al. (2015) · Nature Genetics · doi:10.1038/ng.3412 · Cited by 402
Self-citationDetection of human adaptation during the past 2000 years
Field, Y., Boyle, E. A., Telis, N., Gao, Z., Gaulton, K. J., Golan, D., Yengo, L., Rocheleau, G., Froguel, P., McCarthy, M. I., et al. (2016) · Science · doi:10.1126/science.aag0776 · Cited by 383
Self-citationFast Principal-Component Analysis Reveals Convergent Evolution of ADH1B in Europe and East Asia
Galinsky, K. J., Bhatia, G., Loh, P., Georgiev, S., Mukherjee, S., Patterson, N. J., & Price, A. L. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.12.022 · Cited by 374
Assortative mating, or who marries whom?
Vandenberg, S. G. (1972) · Behavior Genetics · doi:10.1007/bf01065686 · Cited by 368
Sniekers, S., Stringer, S., Watanabe, K., Jansen, P. R., Coleman, J. R. I., Krapohl, E. M. L., Taskesen, E., Hammerschlag, A. R., Okbay, A., Zabaneh, D., et al. (2017) · Nature Genetics · doi:10.1038/ng1017-1558c · Cited by 333
Self-citationGenetic evidence of assortative mating in humans
Robinson, M. R., Kleinman, A., Graff, M., Vinkhuyzen, A. A. E., Couper, D., Miller, M. B., Peyrot, W. J., Abdellaoui, A., Zietsch, B. P., Nolte, I. M., et al. (2017) · Nature Human Behaviour · doi:10.1038/s41562-016-0016 · Cited by 326
Self-citationThe mathematical theory of quantitative genetics.
Bulmer, M. G. (1985) · Cited by 307
ON THE LAWS OF INHERITANCE IN MAN: I. INHERITANCE OF PHYSICAL CHARACTERS
PEARSON, K., & Lee, A. M. (1903) · Biometrika · doi:10.1093/biomet/2.4.357 · Cited by 299
Assortative mating with respect to physical characteristics
Spuhler, J. N. (1968) · Social Biology · doi:10.1080/19485565.1968.9987763 · Cited by 251
Population genetic differentiation of height and body mass index across Europe
Robinson, M. R., Hemani, G., Medina‐Gómez, C., Mezzavilla, M., Esko, T., Shakhbazov, K., Powell, J. E., Vinkhuyzen, A. A. E., Berndt, S. I., Gustafsson, S., et al. (2015) · Nature Genetics · doi:10.1038/ng.3401 · Cited by 233
Self-citationThe effect of assortative mating on the genetic composition of a population
Crow, J. F., & Felsenstein, J. (1968) · Social Biology · doi:10.1080/19485565.1968.9987760 · Cited by 224
Patterns of nonrandom mating within and across 11 major psychiatric disorders
Nordsletten, A. E., Larsson, H., Crowley, J. J., Almqvist, C., Lichtenstein, P., & Mataix-Cols, D. (2016) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.3192 · Cited by 210
SYSTEMS OF MATING. III. ASSORTATIVE MATING BASED ON SOMATIC RESEMBLANCE
Wright, S. (1921) · Genetics · doi:10.1093/genetics/6.2.144 · Cited by 202
Assortative mating by body height and BMI: Finnish Twins and their spouses
Silventoinen, K., Kaprio, J. A., Lahelma, E. T., Viken, R. J., & Rose, R. J. (2003) · American Journal of Human Biology · doi:10.1002/ajhb.10183 · Cited by 196
Married couples' risk of same disease: cross sectional study
Hippisley‐Cox, J., Coupland, C., Pringle, M., Crown, N., & Hammersley, V. (2002) · BMJ · doi:10.1136/bmj.325.7365.636 · Cited by 174
Genetics and educational attainment
Cesarini, D. A., & Visscher, P. M. (2017) · npj Science of Learning · doi:10.1038/s41539-017-0005-6 · Cited by 142
Self-citationBirds of a Feather Do Flock Together
Youyou, W., Stillwell, D. J., Schwartz, H. A., & Kosiński, M. (2017) · Psychological Science · doi:10.1177/0956797616678187 · Cited by 130
Shine, R., O'connor, D., LeMaster, M. P., & Mason, R. T. (2001) · Animal Behaviour · doi:10.1006/anbe.2001.1712 · Cited by 124
Arpana Agrawal, A., Heath, A. C., Grant, J. D., Pergadia, M. L., Statham, D. J., Bucholz, K. K., Martin, N. G., & Madden, P. A. F. (2006) · Behavior Genetics · doi:10.1007/s10519-006-9081-8 · Cited by 119
Assortative mating for human height: A meta‐analysis
Stulp, G., Simons, M. J. P., Grasman, S., & Pollet, T. V. (2017) · American Journal of Human Biology · doi:10.1002/ajhb.22917 · Cited by 96
Ancestry-related assortative mating in Latino populations
RISCH, N. J., Choudhry, S., Vía, M., Basu, A., Sebro, R., Eng, C. S., Beckman, K. B., Thyne, S. M., Chapela, R., Rodríguez‐Santana, J., et al. (2009) · Genome biology · doi:10.1186/gb-2009-10-11-r132 · Cited by 94
Assortative mating and differential fertility by phenotype and genotype across the 20th century
Conley, D., Laidley, T., Belsky, D. W., Fletcher, J. M., Boardman, J. D., & Domingue, B. W. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1523592113 · Cited by 94
Hugh-Jones, D., Verweij, K. J. H., Pourcain, B. S., & Abdellaoui, A. (2016) · Intelligence · doi:10.1016/j.intell.2016.08.005 · Cited by 61
Sebro, R., Hoffman, T. J., Lange, C., Rogus, J. J., & RISCH, N. J. (2010) · Genetic Epidemiology · doi:10.1002/gepi.20528 · Cited by 50
Assortative marriages by body mass index have increased simultaneously with the obesity epidemic
Ajslev, T. A. (2012) · Frontiers in Genetics · doi:10.3389/fgene.2012.00125 · Cited by 39
Genetic determination of height-mediated mate choice
Tenesa, A., Rawlik, K., Navarro, P., & Canela‐Xandri, O. (2015) · Genome biology · doi:10.1186/s13059-015-0833-8 · Cited by 38
Structured mating: Patterns and implications
Sebro, R., Peloso, G. M., Dupuis, J., & RISCH, N. J. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1006655 · Cited by 37
Selecting SNPs to Identify Ancestry
Sampson, J. N., Kídd, K. K., Kidd, J. R., & Zhao, H. (2011) · Annals of Human Genetics · doi:10.1111/j.1469-1809.2011.00656.x · Cited by 29
Assortative mating for a quantitative character
Nagylaki, T. (1982) · Journal of Mathematical Biology · doi:10.1007/bf00275161 · Cited by 23
Height associated variants demonstrate assortative mating in human populations
Li, X., Redline, S. S., Zhang, X., Williams, S. M., & Zhu, X. (2017) · Scientific Reports · doi:10.1038/s41598-017-15864-x · Cited by 14
Quantitative characters under assortative mating: Gametic model
Gimelfarb, A. (1984) · Theoretical Population Biology · doi:10.1016/0040-5809(84)90012-1 · Cited by 7
On the Laws of Inheritance in Man: I. Inheritance of Physical Characters
Pearson, K., & Lee, A. (1903) · Biometrika · doi:10.2307/2331507
Cited by
Sorted by citations
15 years of GWAS discovery: Realizing the promise
Abdellaoui, A., Yengo, L., Verweij, K. J. H., & Visscher, P. M. (2023) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2022.12.011 · Cited by 570
Self-citationWainschtein, P., Jain, D., Zheng, Z., TOPMed Anthropometry Working Group, Aslibekyan, S. W., Becker, D. M., Bi, W., Brody, J. A., Carlson, J. C., Correa, A., et al. (2022) · Nature Genetics · doi:10.1038/s41588-021-00997-7 · Cited by 519
Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects
Howe, L. J., Nivard, M. G., Morris, T. T., Hansen, A. F., Rasheed, H., Cho, Y., Chittoor, G., Ahlskog, R., Lind, P. A., Palviainen, T., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01062-7 · Cited by 377
Self-citationDeconstructing the sources of genotype-phenotype associations in humans
Young, A. I., Benonisdottir, S., Przeworski, M., & Kong, A. (2019) · Science · doi:10.1126/science.aax3710 · Cited by 288
Risk prediction of late-onset Alzheimer’s disease implies an oligogenic architecture
Zhang, Q., Sidorenko, J., Couvy-Duchesne, B., Marioni, R. E., Wright, M. J., Goate, A. M., Marcora, E., Huang, K.-L., Porter, T., Laws, S. M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18534-1 · Cited by 272
Self-citation
Metadata
- Authors
- Yengo, L., Robinson, M. R., Keller, M. C., Kemper, K. E., Yang, Y., Trzaskowski, M., Gratten, J., Turley, P., Cesarini, D., Benjamin, D. J., Wray, N. R., Goddard, M. E., Yang, J., & Visscher, P. M.
- Affiliations
- The University of Queensland (AU)
- University of Colorado Boulder (US)
- Translational Research Institute (AU)
- Broad Institute (US)
- National Bureau of Economic Research (US)
- University of Southern California (US)
- The University of Melbourne (AU)
- Corresponding author
- Visscher, Peter M.
- ORCID
- Venue
- Nature Human Behaviour
- Published
- 2018-11-26
- Volume
- 2
- Issue
- 12
- Pages
- 948-954
- ISSN
- 2397-3374 (ISSN-L)
- PMC
- PMC6705135
- OpenAlex
- W2952585581
- Cited by
- 148
- References
- 54
- Citations by year
- 2026: 12 · 2025: 20 · 2024: 27 · 2023: 22 · 2022: 26 · 2021: 17 · 2020: 9 · 2019: 13 · 2018: 2
- FWCI
- 6.27
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Nature Human Behaviour (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- IRIS (submittedVersion)
- SERVAL (Université de Lausanne) (submittedVersion)
- Funders
- National Institutes of Health
- Medical Research Council (1107258, 1113400, 1078037, 1078901, 1127440, 1103418)
- Australian Research Council (DP160103860, DP160102400, DP130102666, 1113400)
- National Health and Medical Research Council (1113400, 1078901, 1127440, 1107258, 1078037, 1103418)
- National Institute on Aging (RC2AG036607, R56AG042568, R01AG042568)
- National Institute of Mental Health (R01MH100141)
- National Institute of General Medical Sciences (P01GM099568)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Keywords
- assortative mating, mate choice, human genome, single nucleotide polymorphisms, population stratification, height, educational attainment, complex traits, genome organization
- MeSH terms
- Alleles, Body Height, Educational Status, Female, Humans, Male, Marriage, Genome, Human, Quantitative Trait, Heritable, Polymorphism, Single Nucleotide, White People
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review